• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.687-697
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• 2014

This study ranges from planning phase to the detailed design phase of steel box girder bridge and proposes ways to generate semantic information of components through Industry Foundation Classes (IFC), a data model for Building Information Modeling (BIM). The classification of components of steel box girder bridge was performed to define information items required for identifying semantic information based on IFC, and spatial information items based on topology and physical information items based on functions of components were classified to create additional properties that does not support IFC by applying user-defined property set within the IFC framework. Steel box girder bridge information model based on IFC was implemented through BIM software and semantic information input interface, which was developed in this study to examine the effectiveness of the additionally created user-defined property. Furthermore, the quantity take-off of components was performed through information model of steel box girder bridge, and the applicability of the proposed method was tested by comparing the quantity take-off based on design document with the result.

• Korean Journal of Remote Sensing
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• v.34 no.4
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• pp.693-702
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• 2018

With the development of data analysis methods and data processing capabilities, semantic analysis of floorplans has been actively studied. Therefore, studies for extracting text information from drawings have been conducted for semantic analysis. However, existing research that separates rasterized text from floorplan has the problem of loss of text information, because when graphic and text components overlap, text information cannot be extracted. To solve this problem, this study defines the morphological characteristics of the text in the floorplan, and classifies the class of the corresponding region by applying the class of the SIFT key points through the SVM models. The algorithm developed in this study separated text components with a recall of 94.3% in five sample drawings.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.115-121
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• 2009

Web 2.0 has become the face next generation Web among the business world and research community. Web 2.0 is instant superficial gratification of people. On the other hand, Semantic Web is deep, meaningful and lasting relationship with data. So, it is difficult to apply the Semantic Web to the real world. In this paper, a platform for educational services using the Semantic Web and Web 2.0 is proposed. The proposed platform is based mix of the Semantic Web and Web 2.0, so it is useful to apply in the real world applications. Two services are presented, one is a semantic email system and the other is a cyber study space. The cyber study space adjusted each student is presented. The study environment is called iStudySpace that has personal scheduler, study status plan table, personalized search engine and several gadgets. Finally characteristics and limitations of the Semantic Web and Web 2.0, the organization and components of the platform, evaluation of iStudySpace are shown.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1833-1848
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• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.

• The KIPS Transactions:PartB
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• v.19B no.1
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• pp.43-52
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• 2012

Semantic role labeling is the research area analyzing the semantic relationship between elements in a sentence and it is considered as one of the most important semantic analysis research areas in natural language processing, such as word sense disambiguation. However, due to the lack of the relative linguistic resources, Korean semantic role labeling research has not been sufficiently developed. We, in this paper, propose an automatic predicate-argument analyzer to begin constructing the Korean PropBank which has been widely utilized in the semantic role labeling. The analyzer has mainly two components: the semantic lexical dictionary and the automatic predicate-argument extractor. The dictionary has the case frame information of verbs and the extractor is a module to decide the semantic class of the argument for a specific predicate existing in the syntactically annotated corpus. The analyzer developed in this research will help the construction of Korean PropBank and will finally play a big role in Korean semantic role labeling.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.385-392
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• 2001

This paper proposes a meta modeling technique which permits to describe a KBS according to three axis: the object of reuse axis, the levels of granularity axis and the reuse process axis. The object of reuse axis allows to see a KBS as a set of inter-related components for reuse purposes. The levels of granularity axis allows to describe the KBS components according to different levels of granularity for clarity and reuse purposes. The reuse process axis allows to see the KBS components as (re)usable components.

• International Journal of Contents
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• v.10 no.4
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• pp.30-37
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• 2014

The current study was conducted to examine the temporal and spatial activation sequences related to morphosyntactic, semantic and orthographic-lexical sentences, focusing on the morphological-orthographic and lexical-semantic deviation processes in Korean language processing. The Event-related Potentials (ERPs) of 15 healthy students were adopted to explore the processing of head-final critical words in a sentential plausibility task. Specifically, it was examined whether the ERP-pattern to orthographic-lexical violation might show linear precedence over other processes, or the presence of additivity across combined processing components. For the morphosyntactic violation, fronto-central LAN followed by P600 was found, while semantic violation elicited N400, as expected. Activation of P600 was distributed in the left frontal and central sites, while N400 appeared even in frontal sites other than the centro-parietal areas. Most importantly, the orthographic-lexical violation process revealed by earlier N2 with fronto-central activity was shown to be complexes of morphological and semantic functions from the same critical word. The present study suggests that there is a linear precedence over the morphological deviation and its lexical semantic processing based on the immediate possibility of lexical information, followed by sentential semantics. Finally, late syntactic integration processes were completed, showing different topographic activation in order of importance of ongoing sentential information.

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.1
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• pp.1-13
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• 2004

The Semantic Web introduces the next generation of the Web by establishing a semantic layer of machine-understandable data to enable machines (i.e intelligent agents) retrieve more relevant information and execute automated web services using semantic information. Ontology-related technologies are very important to evolve the World Wide Web of today into the Semantic Web in representation and share of semantic data. In this paper, we proposed and implemented the efficient ontology management system, K-Box, which constructs and manages ontologies using topic maps. We can use K-Box system to construct, store and retrieve ontologies. K-Box system has several components: Topicmap Factory, Topicmap Provider, Topicmap Query Processor, Topicmap Object Wrapper, Topicmap Cache Manager, Topicmap Storage Wrapper.

• Journal of Information Science Theory and Practice
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• v.2 no.4
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• pp.61-76
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• 2014

The exponential growth of information on the web far exceeds the capacity of present day information retrieval systems and search engines, making information integration on the web difficult. In order to overcome this, semantic web technologies were proposed by the World Wide Web Consortium (W3C) to achieve a higher degree of automation and precision in information retrieval systems. Semantic web, with its promise to deliver machine understanding to the traditional web, has attracted a significant amount of research from academia as well as from industries. Semantic web is an extension of the current web in which data can be shared and reused across the internet. RDF and ontology are two essential components of the semantic web architecture which support a common framework for data storage and representation of data semantics, respectively. Ontologies being the backbone of semantic web applications, it is more relevant to study various approaches in their application, usage, and integration into web services. In this article, an effort has been made to review the research work being undertaken in the area of design and development of ontology supported information systems. This paper also briefly explains the emerging semantic web technologies and standards.

• 한국디지털정책학회:학술대회논문집
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• 2006.06a
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• pp.355-361
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• 2006

It has lately been recognized that the sharing and exchanging of the research results information is the critical factor to improve the research productivity. So many institutions are planning or developing the information systems which provide the research information services for researcher. But it has very difficulty in integrating the research resources information due to the dispersion and heterogeneity in data sources, and semantic and structural difference in describing data. We propose the semantic web based methodology and conceptual framework for raising the interoperability of metadata about research results information, which will support the integration of the distributed research data for information services in the end. Finally we proposed the conceptual architecture of research information service system which shows the main components, the functional requirements, and the principal and design direction at implementing the system.